Redoing changes for PR 46 (moveit#59)

* Minor fixup

doc/kinematic_model/kinematic_model_tutorial.rst

@@ -38,9 +38,7 @@ Roslaunch the launch file to run the code directly from moveit_tutorials::
 
 Expected Output
 ---------------
-The expected output will be in the following form. The numbers will not match since we are using random joint values
-
-**Note:** Don't worry if your output has different ROS console format. You can customize your ROS console logger by following `this blog post <http://dav.ee/blog/notes/archives/898>`_: ::
+The expected output will be in the following form. The numbers will not match since we are using random joint values: ::
 
  ros.moveit_tutorials: Model frame: /panda_link0
  ros.moveit_tutorials: Joint panda_joint1: 0.000000
@@ -77,7 +75,7 @@ The expected output will be in the following form. The numbers will not match si
             0     -0.74231    -0.669976    -0.367232    -0.662737     0.415389    -0.715607
             1  4.89669e-12    0.0154256     0.862009     0.021077     0.842067    0.0690048
 
-**Note:** Don't worry if your output has different ROS console format. You can customize your ROS console logger by following `this blog post. <http://dav.ee/blog/notes/archives/898>`_
+**Note:** Don't worry if your output has different ROS console format. You can customize your ROS console logger by following `this blog post <http://dav.ee/blog/notes/archives/898>`_.
 
 The Entire Code
 ---------------
@@ -91,4 +89,4 @@ To run the code, you will need a launch file that does two things:
  * Loads the Panda URDF and SRDF onto the parameter server, and
  * Puts the kinematics_solver configuration generated by the MoveIt! Setup Assistant onto the ROS parameter server in the namespace of the node that instantiates the classes in this tutorial.
 
-.. literalinclude:: ./launch/kinematic_model_tutorial.launch
+.. literalinclude:: ./launch/kinematic_model_tutorial.launch

doc/planning_scene_ros_api/src/planning_scene_ros_api_tutorial.cpp

@@ -75,7 +75,7 @@ int main(int argc, char** argv)
   //
   // Advertise the required topic
   // ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  // We create a publisher and wait for there to be subscribers
+  // We create a publisher and wait for subscribers
   // Note that this topic may need to be remapped in the launch file
   ros::Publisher planning_scene_diff_publisher = node_handle.advertise<moveit_msgs::PlanningScene>("planning_scene", 1);
   ros::WallDuration sleep_t(0.5);

doc/planning_with_approximated_constraint_manifolds/planning_with_approximated_constraint_manifolds_tutorial.rst

@@ -6,7 +6,7 @@ Constraints can be defined in joint space and Cartesian space where the latter i
 While planning a trajectory each joint state needs to follow all of the set constraints, which is performed by rejection sampling by default.
 This however might lead to very long planning times, especially when the constraints are very restrictive and the rejection rate is correspondingly high.
 
-`Sujan et al <http://ioan.sucan.ro/files/pubs/constraints_iros2012.pdf>`_ present an approach where they compute an approximation of the constraint manifold beforehand and perform trajectory planning in that.
+`Sucan et al <http://ioan.sucan.ro/files/pubs/constraints_iros2012.pdf>`_ present an approach where they compute an approximation of the constraint manifold beforehand and perform trajectory planning in that.
 The OMPL plugin contains the functionality to do that for a given set of constraints and save it in a database.
 In later instances the database can be loaded to use for constrained planning with any OMPL planner which strongly reduces planning time.